Law enforcement organizations use fingerprints to confirm the identity of assumed crime suspects or to determine the identity of unknown suspects from prints left at a crime scene. A fingerprint left at a crime scene is typically referred to as a latent print, and the search process of the latent print against a fingerprint database is commonly known as a latent search. There are, generally, two types of latent searches. One is a latent print to a ten-print search. The other is a ten-print to unsolved latent search, also known as a reverse search.
With recent advances in AFIS (automatic fingerprint identification system) technology, the performance of the ten-print to ten-print search has been greatly improved. However, latent search remains a challenge, due to the generally poor image quality of latent prints. Image quality is a much more critical factor in latent print searches than in ten-print to ten-print searches because in a latent search there is only one finger that forms the basis of the comparison. However in a ten-print to ten-print search, while a few of the fingers that form the basis of the search may be of poor image quality, typically several others may be of a high enough image quality to enable effective matching.
Besides fingerprint minutiae, features such as ridge count, ridge curvature, minutiae constellations, core, delta, whorl and other such megafeatures as well as additional classification information may be extracted from fingers that have acceptable image quality. In contract, the generally low image quality of a latent print will usually preclude access to many of these features and limit the precision of the remaining. As a consequence, many fingerprint matcher systems cannot be reliably used on latent prints.
Thus, there exists a need for a method and apparatus that can reliably perform latent searches.